Abstract

Lyme disease is the most frequently reported vector borne disease in the United States, and it is endemic to Rhode Island. The high incidence of tick-borne disease in this region results from intense peridomestic human exposure to the vector Ixodes scapularis (a.k.a. blacklegged tick). An increasing number of studies have indicated that Ixodid tick distributions are determined primarily by climate and vegetation, more so than by host-related factors. Environmental conditions play an important role in the survival of I. scapularis since both water stress and, to a lesser extent, temperature are substantial factors regulating off-host mortality. Increased knowledge about the influence of climatic conditions on the spatial and temporal I. scapularis abundance and activity of I. scapularis may enable development of an advanced Lyme disease risk warning system, as well as promote use of tick bite prevention measures. ^ We investigated the hypothesis that the duration of a threshold level of atmospheric moisture directly affects tick activity and survival. To test our hypothesis, a three-pronged approach was implemented, where we: (1) determined if temporal measurements of atmospheric moisture content were correlated with observed levels of tick activity and survival; (2) evaluated if relatively fine-scale measures of atmospheric moisture are required to provide near-real time estimates of RH in tick habitat and predictions of tick activity; and (3) assessed if a multi-sensor approach could be used to relate remotely-sensed Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data to atmospheric moisture conditions affecting tick survival. A two-year field study was established to validate prior laboratory findings of a relative humidity (RH) threshold for nymphal blacklegged tick activity and survival. A network of RH loggers was established among three study areas distributed across a latitudinal gradient for the state of Rhode Island. A hierarchical sampling design was used, scaling from ground measurements of nymphal tick abundance to a remotely sensed index of moisture availability (Temperature-Vegetation Dryness Index). TVDI values, derived from MODIS data, were used to characterize land surface conditions in tick habitat and to determine if limited moisture availability caused a decline in nymphal tick activity and possible mortality as a result of desiccation. Negative binomial regression identified TVDI as a significant predictor of tick abundance during the summer of 2010 (coefficient = -2.481, SE = 0.768, P = 0.0012), but not 2009 (coefficient = 0.332, SE = 0.975, P = 0.7333). Consistent with the literature, the study demonstrated limited success when moisture was not a limiting factor. ^ Ground measurements of both RH and nymphal tick abundance within each study plot, identified two significant moisture parameters across both years: average RH recorded 14 days prior to sampling (AvgRH14, 2009: P = 0.0160; 2010: P =0.0006) and cumulative hours sub-RH threshold recorded seven days prior to sampling (CumHrsSub7day, 2009: P = 0.0003; 2010: P = 0.0112). These two variables were consistent across both study years, despite dramatically different weather patterns. A retrospective analysis, examining 14 years (1997 to 2010) of nymphal blacklegged tick abundance data against the total number of tick-adverse humidity events (TAHEs) (> 8 h) recorded in the month of June successfully predicted total nymphal tick abundance recorded during that same summer (coefficient = -69.57, SE = 27.66, P = <0.027). Years characterized by a greater number of TAHEs in June generally resulted in below average annual nymphal blacklegged tick abundance. Additionally, since tick samples were collected at each study site twice (early season = round one; late season = round two), a significant and positive relationship (coefficient = 0.0344, SE = 0.015, P = 0.040) was identified between the ratio of nymphs collected in round one vs. round two and TAHEs (> 8 h) recorded in June (largely round one), suggesting that TAHEs were an indicator of tick mortality and could be used to predict exposure risk during the same year. Collectively, results from these studies suggest that readily available relative humidity data could be used to predict seasonal trends in Lyme disease risk and could be used as the framework for tick-borne disease risk forecasts.^